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Data Engineer with less than a year in ETL pipelines, cloud data systems, and data analytics.
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Data Analytics and Engineering enthusiast with strong expertise in SQL, Python, and cloud-based data systems. Experienced in working with large datasets, ETL pipelines, and BI tools to generate actionable insights. Skilled in data modeling, dashboard development, and scalable data processing using modern technologies.
Sreyas Institute of Engineering and Technology
Bachelor of Technology · Computer Science and Engineering
August 1, 2022 – June 30, 2026
Mphasis
Associate Software Engineer Intern
December 1, 2025 – April 30, 2026
India
Customer Segmentation Analysis
January 1, 2026 – January 1, 2026
Performed customer segmentation using clustering techniques to group users based on purchasing behavior. Cleaned and preprocessed large datasets, applied K-Means clustering, and visualized customer segments to help identify high-value customers and improve targeted marketing strategies.
Emotion Detection from Speech
January 1, 2026 – January 1, 2026
Developed a speech-based emotion recognition system that classifies human emotions such as happy, sad, angry, and neutral from audio signals. Extracted audio features like MFCC, chroma, and mel spectrogram using Librosa and trained deep learning models for accurate prediction. Improved model performance through data preprocessing and hyperparameter tuning.
Retail Sales Data Pipeline
January 1, 2025 – January 1, 2025
Built a basic ETL pipeline to extract retail sales data, transform it using Python, and load it into structured tables. Used SQL for querying and validating datasets. Simulated real-world data pipeline workflows for reporting and analysis.
Student Performance Prediction
January 1, 2024 – January 1, 2024
Built a predictive model to analyze student performance based on various academic and behavioral factors. Performed data preprocessing, feature selection, and model evaluation to improve prediction accuracy.
Cultural Fit Analysis
The candidate's academic projects show a diverse interest in data-related fields, including retail sales data, emotion detection, student performance, and customer segmentation. The internship at Mphasis, though short, indicates exposure to a professional software development environment and hands-on training in Data Engineering. This breadth of exposure and willingness to learn new technologies aligns well with a culture that values continuous learning and adaptability. However, the experience is primarily academic, and real-world team collaboration beyond academic projects is limited.
Soft Skills & Operational Fit
The candidate demonstrates good communication and teamwork skills through collaborative project descriptions. Their ability to quickly learn and adapt to new technologies, as highlighted in their resume, suggests a good operational fit for dynamic environments. Strong analytical, problem-solving, and debugging skills are also noted.